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    Home»Tech & Innovation»How developers are using Apple’s local AI models with iOS 26
    Tech & Innovation

    How developers are using Apple’s local AI models with iOS 26

    FinsiderBy FinsiderSeptember 26, 2025No Comments4 Mins Read
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    array of iPhones with Apple Intelligence logos above
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    Earlier this year, Apple introduced its Foundation Models framework during WWDC 2025, which allows developers to use the company’s local AI models to power features in their applications.

    The company touted that with this framework, developers gain access to AI models without worrying about any inference cost. Plus, these local models have capabilities such as guided generation and tool calling built in.

    As iOS 26 is rolling out to all users, developers have been updating their apps to include features powered by Apple’s local AI models. Apple’s models are small compared with leading models from OpenAI, Anthropic, Google, or Meta. That is why local-only features largely improve quality of life with these apps rather than introducing major changes to the app’s workflow.

    Below are some of the first apps to tap into Apple’s AI framework.

    Lil Artist

    The Lil Artist app offers various interactive experiences to help kids learn different skills like creativity, math, and music. Developer Arima Jain and Aman Jain shipped an AI story creator with the iOS 26 update. This allows users to select a character and a theme, with the app generating a story using AI. The developer said that the text generation in the story is powered by the local model.

    Image Credits:Lil Artist

    Daylish

    The developer of the Daylish app is working on a prototype for automatically suggesting emojis for timeline events based on the title for the daily planner app.

    MoneyCoach

    Finance tracking app MoneyCoach has two neat features powered by local models. First, the app shows insights about your spending, such as whether you spent more than average on groceries for that particular week. The other feature automatically suggests categories and subcategories for a spending item for quick entries.

    A screenshot of financial tracking app MoneyCoach where the screen shows summary of accounts and shows a weekly insight on grocery spend for the week.
    Image Credits:MoneyCoach

    LookUp

    The word learning app LookUp has added two new modes using Apple’s AI models. There is a new learning mode, which leverages a local model to create examples corresponding to a word. Plus, the example asks users to explain the usage of the word in a sentence.

    A screenshot of LookUp word learning app that shows a screen that displays an example to understand a new word
    Image Credits:LookUp

    The developer is also using on-device models to generate a map view of a word’s origin.

    A screenshot of the Lookup app with a map view showing origin of a word.
    Image Credits:Lookup

    Tasks

    Just like a few other apps, the Tasks app implemented a feature to suggest tags for an entry using local models automatically. It’s also using these models to detect a recurring task and schedule it accordingly. And the app lets users speak a few things and use the local model to break them down into various tasks without using the internet.

    This is a lifestyle shot of Tasks app showing screen with a new feautre that uses local models to suggest tags when you enter a task.
    Image Credits:Tasks

    Day One

    Automattic-owned journaling app Day One is using Apple’s models to get highlights and suggest titles for your entry. The team has also implemented a feature to generate prompts that nudge you to dive deeper and write more based on what you have already written.

    A screenshot showing Day One journaling app's features implemented using Apple's local model. These features include a summary, title suggestion, and prompt generation to go deeper into writing.
    Image Credits:Day One

    Crouton

    Recipe app Crouton is using Apple Intelligence to suggest tags for a recipe and assign names to timers. It also uses AI to break down a block of text into easy-to-follow steps for cooking.

    SignEasy

    Digital signing app SignEasy is using Apple’s local models to extract key insights from a contract and give users a summary of the document they are signing.

    Dark Noise

    Background sound app Dark Noise has used Apple’s local models to let users describe a soundscape in a few words and generate one based on that. You can adjust the levels of different elements of the soundscape once it is created.

    Lights Out

    The new app to track the F1 season and grand prix from Shihab Mehboob, developer of Twitter client Avery and Mastodon client Mammoth. Lights Out is using on-device AI models to summarize commentary during a race.

    Capture

    Note-taking app Capture is using local AI to show category suggestions to users as they type in their notes or tasks.

    Image Credits: Capture

    Lumy

    Sun and weather tracking app Lumy now shows neat weather-related suggestions on the app using AI.

    Image Credits: Lumy

    Cardpointers

    Cardpointers is an app that helps you track your credit card expenses and also gives suggestions on the best way to earn points from the cards you have. The app’s new version is using AI to let users ask questions about their cards and offers.

    Image Credits: Cardpointers

    Guitar Wiz

    The guitar learning app is using the Apple Foundation Model framework in a few ways. Users will see an explanation of a chord while learning it. The app is showing advanced players’ insights based on time intervals. Plus, the AI model is helping the developer support over 15 languages.

    We will continue updating this list as we discover more apps using Apple’s local models.

    Apples developers iOS local models
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